metadata
tags:
- spacy
- token-classification
language:
- es
license: gpl-3.0
model-index:
- name: es_cantemist_ner_trf
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.8487622923
- name: NER Recall
type: recall
value: 0.8416274378
- name: NER F Score
type: f_score
value: 0.8451798075
widget:
- text: >-
JUICIO DIAGNÓSTICO Encefalitis límbica y polineuropatía sensitiva
paraneoplásicas secundarias a carcinoma microcítico de pulmón cTxN2 M0
(enfermedad limitada) .
Basic Spacy BioNER pipeline, with a RoBERTa-based model [bsc-bio-ehr-es] (https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es) and a dataset, CANTEMIST, annotated with tumour morphology entities. For further information, check the official website. Visit our GitHub repository. This work was funded by the Spanish State Secretariat for Digitalization and Artificial Intelligence (SEDIA) within the framework of the Plan-TL
| Feature | Description |
|---|---|
| Name | es_cantemist_ner_trf |
| Version | 3.4.0 |
| spaCy | >=3.4.0,<3.5.0 |
| Default Pipeline | transformer, ner |
| Components | transformer, ner |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | https://huggingface.co/datasets/PlanTL-GOB-ES/cantemist-ner |
| License | [Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0) |
| Author | The Text Mining Unit from Barcelona Supercomputing Center. |
| Copyright | Copyright by the Spanish State Secretariat for Digitalization and Artificial Intelligence (SEDIA) (2022) |
| Funding | This work was funded by the Spanish State Secretariat for Digitalization and Artificial Intelligence (SEDIA) within the framework of the Plan-TL |
Label Scheme
View label scheme (1 labels for 1 components)
| Component | Labels |
|---|---|
ner |
MORFOLOGIA_NEOPLASIA |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
84.52 |
ENTS_P |
84.88 |
ENTS_R |
84.16 |
TRANSFORMER_LOSS |
25646.78 |
NER_LOSS |
9622.84 |